New wireless tech from MIT promises password-free Wi-Fi
It could also help make smart homes smarter
By Katherine Noyes
PCWorldMar 31, 2016 8:50 am PDT
New wireless technology developed by researchers at MIT’s Computer Science and Artificial Intelligence Lab promises to kill the Wi-Fi password at last.
Dubbed Chronos, the new system enables a single Wi-Fi access point to locate users to within tens of centimeters without relying on any external sensors. What that means is that it could figure out where people are in a home or office and adjust heating and cooling accordingly. It could also enable a small cafe to better restrict its free Wi-Fi to paying customers.
Existing Wi-Fi devices don’t have wide enough bandwidth to measure the “time of flight” of a signal from transmitter to receiver, or router to device, so typically a person’s position can be determined only by triangulating multiple angles relative to the person from multiple access points.
Chronos, on the other hand, can compute time of flight with an average error of just 0.47 nanoseconds, MIT said, making it 20 times more accurate than existing systems. In fact, by multiplying the time of flight by the speed of light, Chronos can calculate not just the angle, but the actual distance from a user to an access point.
“Knowing both the distance and the angle allows you to compute the user’s position using just one access point,” said MIT PhD student Deepak Vasisht. “This is encouraging news for the many small businesses and consumers that don’t have the luxury of owning several access points.”
Making it all possible was Vasisht’s observation that signals travel over the air from transmitter to receiver at a different frequency than they do within a Wi-Fi device during the process of being detected, said Dina Katabi, an MIT professor who led the research team, in an interview on Tuesday.
After coming up with an algorithm to exploit that fact, the researchers tested the technology in a two-bedroom apartment with four occupants and found that Chronos can correctly identify which room a resident is in 94 percent of the time. In a cafe, it was 97 percent accurate in distinguishing in-store customers from out-of-store intruders, meaning that passwords could be eliminated.
They also demonstrated a drone that maintains a safe distance from its user with a margin of error of about four centimeters.
Vasisht presented a paper summarizing the findings earlier this month at the USENIX Symposium on Networked Systems Design and Implementation.